Touch Sensor Jump Detection and Virtual Position Calculation
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Solution Overview
Problem
Capacitive touch sensors often experience position calculation errors, such as 'jags' when fingers move across the surface, leading to false button triggers and improper gesture recognition, particularly when multiple fingers are close together or cover a larger area than the centroid matrix can account for.
Innovation Solution
A touch-sensitive device with logic to detect position jumps and calculate virtual positions based on previous real and virtual touches, using distance and center-range tests to adjust coordinates and update positions, thereby reducing errors in multi-touch scenarios.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a 3×3 centroid matrix is used for touch position calculation, then the calculation is simple and fast, but the position accuracy deteriorates when touches cover a larger area or when multiple touches are close together
Solution Approach 1:
The patent dynamically adjusts the centroid matrix size based on the detected touch area. When touches cover a larger area, the system automatically increases the matrix size (e.g., from 3×3 to 5×5 or larger) to capture all relevant sensor signals. This dynamic adaptation resolves the contradiction by maintaining calculation efficiency for small touches while improving accuracy for larger touch areas.
Solution Approach 2:
The system changes the parameter of centroid matrix size according to touch conditions. By monitoring touch area and distribution, the algorithm selects appropriate matrix sizes (3×3, 5×5, 7×7, or larger) to optimize position calculation accuracy for different scenarios, thereby resolving the fixed-size limitation.
2Measurement precision
If a larger centroid matrix is used for touch position calculation, then the position accuracy improves for larger touch areas, but the calculation becomes inaccurate when two or more different touches are spaced closely together
Solution Approach 1:
The patent segments the touch surface into multiple independent calculation zones, each with its own centroid matrix. When multiple touches are detected, the system divides them into separate groups and applies appropriate centroid calculations to each group independently. This segmentation prevents interference between close touches while maintaining accuracy for each individual touch.
Solution Approach 2:
The system applies different centroid matrix sizes to different local regions based on touch characteristics. Each touch or touch group receives a customized calculation approach tailored to its specific area and distribution, optimizing accuracy locally without compromising multi-touch resolution globally.
3Strength
If the touch covers a larger area than the centroid matrix can account for, then the signal strength increases, but the calculated position becomes inaccurate because signals from outside the calculation area are not considered
Solution Approach 1:
The patent implements dynamic matrix sizing that automatically expands to match the touch area. When touches cover a larger area, the system increases the centroid matrix size proportionally to ensure all relevant sensor signals are included in the calculation. This dynamic scaling maintains both signal strength utilization and position accuracy.
Solution Approach 2:
The system changes the centroid matrix size parameter based on the detected touch area extent. By monitoring the spatial distribution of touch signals, the algorithm selects an appropriate matrix size that fully encompasses the touch area, ensuring all contributing signals are captured for accurate position calculation.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach improves the accuracy of touch position calculations, reducing errors and enhancing gesture recognition by correctly determining virtual positions even when fingers are close together or move across the sensor surface, thus preventing false triggers and improving overall device operation.
Implementation Method 1
Capacitive sensing is a technology based on capacitive coupling that is used in many different types of sensors, including those to detect and measure touch and gestures on surfaces
Implementation Method 2
Bringing a finger or conductive stylus near the surface of the sensor changes the local electric field which reduces the mutual capacitance
Data Source
AI summary
A method includes scanning touch sensors to obtain sensor readings; performing jump detection on the sensor readings; and if a jump is detected, calculating at least one virtual position from the sensor readings using a distance to coordinates the precede those of the detected jump.